Nearly every goods and services provider offers some degree of support to those customers who buy or user their products and/or services. Support can come in many forms using various mediums, such as a phone call, video chat, email, a messenger service, etc. Having a respectable customer support system can play an integral role in building/maintaining a company's brand. As such, companies often go to great lengths to ensure their customer's support needs are met. To meet those support needs, companies employ any number of customer service agents. Oftentimes, the customer service agents are assigned to a physical cubicle at a co-location center and work a set schedule.
However, such work accommodations are not likely to be scalable. In other words, the support staff is not dynamic such that it can be scaled based on demand. Presently, in order to deal with such changes, management has to make a judgment call as to how to handle the work flow. For example, agents may be released before their shift ends if call volume is too low, they may be asked to work past their shift if call volume is too high, they can be called in to work on an off-day, etc. Unfortunately, such decisions can have serious consequences. For example, if call volume is slow, resulting in the call center being overstaffed, one or more agents is likely to be sent home. However, it is reasonable to expect that call volumes can increase/decrease unexpectedly at any given time. Under such conditions, call volume can exceed support capacity, in which case the customer service responsiveness is negatively impacted. Such consequences can result in tarnishing the company's brand or worse, depending on the support services being provided. Accordingly, there exists a need for improvements in technologies for call center scalability.